In transportation systems, it is desirable to count the number of wheels and axles with respect to a vehicle for classification purposes. Conventional sensing approaches utilize a mechanical treadle device or an inductive loop buried in a pavement along with signal processing to estimate these entities. The treadles are mechanical devices and as such subject to wear, degradation by environment and other issues and requires high maintenance. An inductive loop counting method is indirect and only infers results based on averages. Hence, slight differences in vehicle design and construction may result in supplying erroneous counts. Neither of these techniques can count the number of wheels, only the number of axles. Also, human classifiers are often required to avoid inaccurate counts.
Based on the foregoing, it is believed that a need exists for an improved approach for counting a vehicle wheel and axle, as described in greater detail herein.